Patient populations in many clinical trials are heterogeneous with respect to disease manifestation, drug response, and pharmacological profile. Investigation into subgroups of a patient population has become indispensable step in a clinical trial to understand the heterogeneity. Advancements in biomarker biotechnologies such as omics have provided new opportunities to investigate subgroups according to patients’ molecular profiles. Numerous statistical methodologies and strategies in subgroup analysis have been proposed leveraging those biomarker information in the last decade, however, challenges remain in many areas including control of false positives/negatives, interpretation of subgroups discovered, validity of regulatory claim, implications of business decisions and regulatory approval, and impact on product labeling and prescribing decisions etc. In this session, a comprehensive review of new methods of biomarker and subgroup identification for personalized medicine will be presented. Novel statistical methods for subgroup identification will be introduced. Complications and limitations in the regulatory context will also be discussed.